237 lines
7.1 KiB
Python
237 lines
7.1 KiB
Python
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import os
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import sys
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# add python path of PaddleDetection to sys.path
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parent_path = os.path.abspath(os.path.join(__file__, *(['..'] * 2)))
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sys.path.insert(0, parent_path)
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# ignore warning log
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import warnings
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warnings.filterwarnings('ignore')
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import glob
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import ast
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import paddle
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from ppdet.core.workspace import load_config, merge_config
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from ppdet.engine import Trainer
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from ppdet.utils.check import check_gpu, check_npu, check_xpu, check_mlu, check_version, check_config
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from ppdet.utils.cli import ArgsParser, merge_args
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from ppdet.slim import build_slim_model
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from ppdet.utils.logger import setup_logger
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logger = setup_logger('train')
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def parse_args():
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parser = ArgsParser()
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parser.add_argument(
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"--infer_dir",
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type=str,
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default=None,
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help="Directory for images to perform inference on.")
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parser.add_argument(
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"--infer_img",
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type=str,
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default="../2_compile/qtset/coco/000000000139.jpg",
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help="Image path, has higher priority over --infer_dir")
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parser.add_argument(
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"--output_dir",
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type=str,
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default="output/infer",
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help="Directory for storing the output visualization files.")
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parser.add_argument(
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"--draw_threshold",
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type=float,
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default=0.5,
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help="Threshold to reserve the result for visualization.")
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parser.add_argument(
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"--slim_config",
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default=None,
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type=str,
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help="Configuration file of slim method.")
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parser.add_argument(
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"--use_vdl",
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type=bool,
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default=False,
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help="Whether to record the data to VisualDL.")
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parser.add_argument(
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'--vdl_log_dir',
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type=str,
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default="vdl_log_dir/image",
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help='VisualDL logging directory for image.')
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parser.add_argument(
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"--save_results",
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type=bool,
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default=False,
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help="Whether to save inference results to output_dir.")
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parser.add_argument(
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"--slice_infer",
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action='store_true',
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help="Whether to slice the image and merge the inference results for small object detection."
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)
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parser.add_argument(
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'--slice_size',
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nargs='+',
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type=int,
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default=[640, 640],
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help="Height of the sliced image.")
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parser.add_argument(
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"--overlap_ratio",
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nargs='+',
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type=float,
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default=[0.25, 0.25],
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help="Overlap height ratio of the sliced image.")
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parser.add_argument(
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"--combine_method",
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type=str,
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default='nms',
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help="Combine method of the sliced images' detection results, choose in ['nms', 'nmm', 'concat']."
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)
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parser.add_argument(
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"--match_threshold",
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type=float,
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default=0.6,
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help="Combine method matching threshold.")
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parser.add_argument(
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"--match_metric",
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type=str,
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default='ios',
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help="Combine method matching metric, choose in ['iou', 'ios'].")
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parser.add_argument(
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"--visualize",
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type=ast.literal_eval,
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default=True,
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help="Whether to save visualize results to output_dir.")
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args = parser.parse_args()
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return args
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def get_test_images(infer_dir, infer_img):
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"""
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Get image path list in TEST mode
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"""
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assert infer_img is not None or infer_dir is not None, \
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"--infer_img or --infer_dir should be set"
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assert infer_img is None or os.path.isfile(infer_img), \
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"{} is not a file".format(infer_img)
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assert infer_dir is None or os.path.isdir(infer_dir), \
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"{} is not a directory".format(infer_dir)
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# infer_img has a higher priority
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if infer_img and os.path.isfile(infer_img):
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return [infer_img]
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images = set()
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infer_dir = os.path.abspath(infer_dir)
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assert os.path.isdir(infer_dir), \
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"infer_dir {} is not a directory".format(infer_dir)
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exts = ['jpg', 'jpeg', 'png', 'bmp']
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exts += [ext.upper() for ext in exts]
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for ext in exts:
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images.update(glob.glob('{}/*.{}'.format(infer_dir, ext)))
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images = list(images)
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assert len(images) > 0, "no image found in {}".format(infer_dir)
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logger.info("Found {} inference images in total.".format(len(images)))
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return images
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def run(FLAGS, cfg):
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# build trainer
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trainer = Trainer(cfg, mode='test')
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# load weights
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trainer.load_weights(cfg.weights)
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# get inference images
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images = get_test_images(FLAGS.infer_dir, FLAGS.infer_img)
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# inference
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if FLAGS.slice_infer:
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trainer.slice_predict(
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images,
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slice_size=FLAGS.slice_size,
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overlap_ratio=FLAGS.overlap_ratio,
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combine_method=FLAGS.combine_method,
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match_threshold=FLAGS.match_threshold,
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match_metric=FLAGS.match_metric,
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draw_threshold=FLAGS.draw_threshold,
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output_dir=FLAGS.output_dir,
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save_results=FLAGS.save_results,
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visualize=FLAGS.visualize)
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else:
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trainer.predict(
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images,
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draw_threshold=FLAGS.draw_threshold,
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output_dir=FLAGS.output_dir,
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save_results=FLAGS.save_results,
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visualize=FLAGS.visualize)
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def main():
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FLAGS = parse_args()
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cfg = load_config(FLAGS.config)
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merge_args(cfg, FLAGS)
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merge_config(FLAGS.opt)
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# disable npu in config by default
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if 'use_npu' not in cfg:
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cfg.use_npu = False
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# disable xpu in config by default
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if 'use_xpu' not in cfg:
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cfg.use_xpu = False
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if 'use_gpu' not in cfg:
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cfg.use_gpu = False
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# disable mlu in config by default
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if 'use_mlu' not in cfg:
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cfg.use_mlu = False
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if cfg.use_gpu:
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place = paddle.set_device('gpu')
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elif cfg.use_npu:
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place = paddle.set_device('npu')
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elif cfg.use_xpu:
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place = paddle.set_device('xpu')
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elif cfg.use_mlu:
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place = paddle.set_device('mlu')
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else:
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place = paddle.set_device('cpu')
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if FLAGS.slim_config:
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cfg = build_slim_model(cfg, FLAGS.slim_config, mode='test')
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check_config(cfg)
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check_gpu(cfg.use_gpu)
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check_npu(cfg.use_npu)
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check_xpu(cfg.use_xpu)
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check_mlu(cfg.use_mlu)
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check_version()
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run(FLAGS, cfg)
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if __name__ == '__main__':
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main()
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